The nervous system faces an extremely difficult task: it must be flexible, both during development and in adult life, so that it can respond to a variety of environmental demands and produce adaptive behavior. At the same time, it must be stable, so that the neural circuits that produce behavior function throughout the lifetime of the animal, and so that stable changes produced by learning endure. We are only beginning to understand how neural networks strike a balance between altering individual neurons and synapses in the name of plasticity, while maintaining long-term stability in neural system function. This homeostatic plasticity of neural networks could play a major role in functioning nervous systems. I propose to use the crustacean stomatogastric ganglion (STG), a central pattern generator which is one of the most well characterized neural networks, to investigate the mechanisms underlying homeostatic plasticity in neural networks. One possible outcome of this research is that different mechanisms will be discovered within a network that produces the same behavioral output. If this is the case, this will be one of the first demonstrations of multiple convergent mechanisms for vital behavior in a neural network of any kind. This study also proposed to begin molecular analyses of homeostatic plasticity in the STG by performing the first microarray experiments on crustacean neural function.